A5081727011- Genetic Neurodegenerative Diseases
- EEG and Brain-Computer Interfaces
- Parkinson's Disease Mechanisms and Treatments
- Neurological disorders and treatments
- Neuroscience and Neural Engineering
- Psychosomatic Disorders and Their Treatments
- Advanced Memory and Neural Computing
- Functional Brain Connectivity Studies
- Voice and Speech Disorders
- Blind Source Separation Techniques
- Schizophrenia research and treatment
- Muscle activation and electromyography studies
- Neural dynamics and brain function
- Gaze Tracking and Assistive Technology
- Digital Mental Health Interventions
- Dementia and Cognitive Impairment Research
- Botulinum Toxin and Related Neurological Disorders
- Mental Health Treatment and Access
Roche (Switzerland)
2018-2025
Agency for Science, Technology and Research
2012-2015
University of Freiburg
2015
National University of Singapore
2011-2014
Institute for Infocomm Research
2012-2014
Abstract Digital health technologies enable remote and therefore frequent measurement of motor signs, potentially providing reliable valid estimates sign severity progression in Parkinson’s disease (PD). The Roche PD Mobile Application v2 was developed to measure bradykinesia, bradyphrenia speech, tremor, gait balance. It comprises 10 smartphone active tests (with ½ administered daily), as well daily passive monitoring via a smartwatch. studied 316 early-stage participants who performed at...
Background Remote monitoring of Huntington disease (HD) signs and symptoms using digital technologies may enhance early clinical diagnosis tracking progression, guide treatment decisions, monitor response to disease-modifying agents. Several recent studies in neurodegenerative diseases have demonstrated the feasibility symptom monitoring. Objective The aim this study was evaluate a novel smartwatch- smartphone-based platform remotely HD. Methods This analysis aimed determine reliability...
Abstract Remote digital monitoring of Huntington’s disease (HD) has potential to enhance the development therapeutics, but no data-driven motor score exists quantify diversity manifestations and track their progression. The Disease Digital Motor progression Score (HDDMS), co-designed by people with HD neurologists, is a composite for measuring in clinical research. It derived from smartphone sensor-based tests included remote platform. Developing HDDMS involved selecting features that test...
Non-stationarity of electroencephalograph (EEG) data from session-to-session transfer is one the challenges for EEG-based brain-computer interface systems, which can inversely affect their performance. Among methods proposed to address non-stationarity, adaptation a promising method. In this study, an adaptive extreme learning machine (AELM) update initial classifier calibration session by using chunks EEG evaluation whereby common spatial pattern (CSP) algorithm used extract most...
Studies had shown that Motor Imagery-based Brain Computer Interface (MI-based BCI) system can be used as a therapeutic tool such for stroke rehabilitation, but not all subjects could perform MI well. also and passive movement (PM) similarly activate the motor system. Although idea of calibrating MI-based BCI from PM data is promising, there an inherent difference between features extracted PM. Therefore, need online learning to alleviate improve performance. Hence, in this study we propose...
Background: We aimed to develop a Human Activity Recognition (HAR) model using wrist-worn device assess patient activity in relation negative symptoms of schizophrenia. Methods: Data were analyzed randomized, three-way cross-over, proof-of-mechanism study (ClinicalTrials.gov: NCT02824055) comparing two doses RG7203 with placebo, given as adjunct stable antipsychotic treatment, patients chronic schizophrenia and moderate levels symptoms. Baseline assessed the Positive Negative Syndrome Scale...
The subjects' performance in using a brain-computer interface (BCI) system controlled by motor imagery (MI) varies considerably. Poor performance, known as BCI deficiency, can be due to the inability modulate their sensorimotor rhythms (SMRs). In this work, we investigated feasibility of improving through neurofeedback (NF) training resting state alpha rhythm (8-13 Hz). Thirteen healthy subjects were recruited and randomly assigned experimental or control group. group participated MI-BCI...
The brain signals are generally measured by Electroencephalogram (EEG) in Brain-Computer Interface (BCI) applications. In motor imagery-based BCI, the performed MI tasks (e.g., imagined hand movement) identified through a classification algorithm to communicate and control device. Consequently, improving performance of classifier is crucial success BCI system. One most popular linear applications Support Vector Machine (SVM). This paper improves MI-based finding optimum free kernel...
The aim of this study is to evaluate the ability smartphone-based remote testing meaningfully quantify signs, symptoms and impairments among participants with premanifest Huntington's disease (HD) manifest HD compare them healthy controls (HC).
<h3>Background</h3> Smartphones, wearables and other consumer technology have high-quality sensors that enable the objective, remote, continuous longitudinal measurement of disease symptoms. This approach has potential to be used in future drug development clinical practice. <h3>Aim</h3> In this study, we are exploring feasibility using smartphone wrist-worn for high-frequency monitoring motor non-motor Huntington's (HD) <h3>Method</h3> Patients with HD ongoing ISIS 443139-CS2 study (planned...
To determine the reliability and convergent validity of a novel digital biomarker smartphone application for objective, daily assessment cognition motor symptoms in Huntington's disease (HD).
Abstract Digital health technologies (DHTs) enable remote and therefore frequent measurement of motor signs, potentially providing reliable valid estimates sign severity progression in Parkinson’s disease (PD). The Roche PD Mobile Application v1 was revised to v2 include more measures bradykinesia, bradyphrenia speech tests, optimize suitability for early-stage PD. It studied 316 participants who performed daily active tests at home then carried a smartphone wore smartwatch throughout the...
<sec> <title>BACKGROUND</title> Remote monitoring of Huntington disease (HD) signs and symptoms using digital technologies may enhance early clinical diagnosis tracking progression, guide treatment decisions, monitor response to disease-modifying agents. Several recent studies in neurodegenerative diseases have demonstrated the feasibility symptom monitoring. </sec> <title>OBJECTIVE</title> The aim this study was evaluate a novel smartwatch- smartphone-based platform remotely HD....